Convert a rds file to parquet format

This function allows to convert a rds file to parquet format.

Two conversions possibilities are offered :

• Convert to a single parquet file. Argument `path_to_parquet` must then be used;

• Convert to a partitioned parquet file. Additionnal arguments `partition` and `partitioning` must then be used;

Usage

rds_to_parquet(
  path_to_file,
  path_to_parquet,
  partition = "no",
  compression = "snappy",
  compression_level = NULL,
  ...
)

Arguments

path_to_file

String that indicates the path to the input file (don't forget the extension).

path_to_parquet

String that indicates the path to the directory where the parquet files will be stored.

partition

String ("yes" or "no" - by default) that indicates whether you want to create a partitioned parquet file. If "yes", `"partitioning"` argument must be filled in. In this case, a folder will be created for each modality of the variable filled in `"partitioning"`. Be careful, this argument can not be "yes" if `max_memory` or `max_rows` argument are not NULL.

compression

compression algorithm. Default "snappy".

compression_level

compression level. Meaning depends on compression algorithm.

...

additional format-specific arguments, see arrow::write_parquet() and arrow::write_dataset() for more informations.

Value

A parquet file, invisibly

Examples

# Conversion from a local rds file to a single parquet file ::

rds_to_parquet(
  path_to_file = system.file("extdata","iris.rds",package = "parquetize"),
  path_to_parquet = tempfile(fileext = ".parquet")
)
#> Reading data...
#> Writing data...
#> ✔ Data are available in parquet file under /tmp/RtmpHNodKR/file164832307419.parquet
#> Writing data...

#> Reading data...


# Conversion from a local rds file to a partitioned parquet file  ::

rds_to_parquet(
  path_to_file = system.file("extdata","iris.rds",package = "parquetize"),
  path_to_parquet = tempfile(fileext = ".parquet"),
  partition = "yes",
  partitioning =  c("Species")
)
#> Reading data...
#> Writing data...
#> ✔ Data are available in parquet dataset under /tmp/RtmpHNodKR/file1648b0d057b.parquet
#> Writing data...

#> Reading data...